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Application of chaos-based chaotic invasive weed optimization techniques for environmental OPF problems in the power system

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  • Ghasemi, Mojtaba
  • Ghavidel, Sahand
  • Aghaei, Jamshid
  • Gitizadeh, Mohsen
  • Falah, Hasan

Abstract

This paper presents efficient chaotic invasive weed optimization (CIWO) techniques based on chaos for solving optimal power flow (OPF) problems with non-smooth generator fuel cost functions (non-smooth OPF) with the minimum pollution level (environmental OPF) in electric power systems. OPF problem is used for developing corrective strategies and to perform least cost dispatches. However, cost based OPF problem solutions usually result in unattractive system gaze emission issue (environmental OPF). In the present paper, the OPF problem is formulated by considering the emission issue. The total emission can be expressed as a non-linear function of power generation, as a multi-objective optimization problem, where optimal control settings for simultaneous minimization of fuel cost and gaze emission issue are obtained. The IEEE 30-bus test power system is presented to illustrate the application of the environmental OPF problem using CIWO techniques. Our experimental results suggest that CIWO techniques hold immense promise to appear as efficient and powerful algorithm for optimization in the power systems.

Suggested Citation

  • Ghasemi, Mojtaba & Ghavidel, Sahand & Aghaei, Jamshid & Gitizadeh, Mohsen & Falah, Hasan, 2014. "Application of chaos-based chaotic invasive weed optimization techniques for environmental OPF problems in the power system," Chaos, Solitons & Fractals, Elsevier, vol. 69(C), pages 271-284.
    • Handle: RePEc:eee:chsofr:v:69:y:2014:i:c:p:271-284
    DOI: 10.1016/j.chaos.2014.10.007
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    References listed on IDEAS

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    1. Ghasemi, Mojtaba & Ghavidel, Sahand & Ghanbarian, Mohammad Mehdi & Gharibzadeh, Masihallah & Azizi Vahed, Ali, 2014. "Multi-objective optimal power flow considering the cost, emission, voltage deviation and power losses using multi-objective modified imperialist competitive algorithm," Energy, Elsevier, vol. 78(C), pages 276-289.
    2. Jourdan, L. & Basseur, M. & Talbi, E.-G., 2009. "Hybridizing exact methods and metaheuristics: A taxonomy," European Journal of Operational Research, Elsevier, vol. 199(3), pages 620-629, December.
    3. Ghasemi, Mojtaba & Ghavidel, Sahand & Akbari, Ebrahim & Vahed, Ali Azizi, 2014. "Solving non-linear, non-smooth and non-convex optimal power flow problems using chaotic invasive weed optimization algorithms based on chaos," Energy, Elsevier, vol. 73(C), pages 340-353.
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    1. Jalel Ben Hmida & Mohammad Javad Morshed & Jim Lee & Terrence Chambers, 2018. "Hybrid Imperialist Competitive and Grey Wolf Algorithm to Solve Multiobjective Optimal Power Flow with Wind and Solar Units," Energies, MDPI, vol. 11(11), pages 1-23, October.

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